R ES E A RC H | R E PO R TS
RE FE RENCES AND N OT ES
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ACKN OWLED GMEN TS
Electron microscopy was performed at the University of Utah and
the University of California. We thank D. Belnap (University of
Utah) and M. Braunfeld (University of California, San Francisco) for
supervision of the electron microscopes; A. Orendt and the Utah
Center for High Performance Computing and the NSF Extreme
Science and Engineering Discovery Environment consortium for
computational support; D. Sidote (University of Texas at Austin)
for help processing RNA-seq data; and D. Herschlag and
P. Harbury for helpful comments. Amino acid analysis was
performed by J. Shulze at the University of California, Davis
Proteomics Core. Edman sequencing was performed at Stanford
University’s Protein and Nucleic Acid Facility by D. Winant. This
work was supported by the Searle Scholars Program (A.F.);
Stanford University (O.B.); NIH grants 1DP2GM110772-01 (A.F.),
GM37949, and GM37951 (A.M.L.); the Center for RNA Systems
Biology grants P50 GM102706 (J.S.W.) and U01 GM098254
(J.S.W.); and the Howard Hughes Medical Institute (J.S.W.).
The authors declare no competing financial interests. The
cryo-EM structures have been deposited at the Electron
Microscopy Data Bank (accession codes 2811, 2812, 6169, 6170,
6171, 6172, 6176, and 6201).
SUPPLEMENTARY MATERIALS
www.sciencemag.org/content/347/6217/75/suppl/DC1
Materials and Methods
Figs. S1 to S13
Table S1
References (27–41)
7 August 2014; accepted 14 November 2014
10.1126/science.1259724
CANCER ETIOLOGY
Variation in cancer risk among
tissues can be explained by the
number of stem cell divisions
Cristian Tomasetti1* and Bert Vogelstein2*
Some tissue types give rise to human cancers millions of times more often than other
tissue types. Although this has been recognized for more than a century, it has never been
explained. Here, we show that the lifetime risk of cancers of many different types is strongly
correlated (0.81) with the total number of divisions of the normal self-renewing cells
maintaining that tissue’s homeostasis. These results suggest that only a third of the variation
in cancer risk among tissues is attributable to environmental factors or inherited
predispositions. The majority is due to “bad luck,” that is, random mutations arising during
DNA replication in normal, noncancerous stem cells. This is important not only for
understanding the disease but also for designing strategies to limit the mortality it causes.
E
xtreme variation in cancer incidence across
different tissues is well known; for example, the lifetime risk of being diagnosed
with cancer is 6.9% for lung, 1.08% for
thyroid, 0.6% for brain and the rest of the
nervous system, 0.003% for pelvic bone and
0.00072% for laryngeal cartilage (1–3). Some of
these differences are associated with well-known
risk factors such as smoking, alcohol use, ultraviolet light, or human papilloma virus (HPV)
(4, 5), but this applies only to specific populations
1
Division of Biostatistics and Bioinformatics, Department of
Oncology, Sidney Kimmel Cancer Center, Johns Hopkins
University School of Medicine and Department of
Biostatistics, Johns Hopkins Bloomberg School of Public
Health, 550 North Broadway, Baltimore, MD 21205, USA.
2
Ludwig Center for Cancer Genetics and Therapeutics
and Howard Hughes Medical Institute, Johns Hopkins
Kimmel Cancer Center, 1650 Orleans Street, Baltimore,
MD 21205, USA.
*Corresponding author. E-mail: [email protected] (C.T.);
[email protected] (B.V.)
Corrected 23 January 2015; see full text.
exposed to potent mutagens or viruses. And such
exposures cannot explain why cancer risk in
tissues within the alimentary tract can differ by
as much as a factor of 24 [esophagus (0.51%),
large intestine (4.82%), small intestine (0.20%),
and stomach (0.86%)] (3). Moreover, cancers of
the small intestinal epithelium are three times
less common than brain tumors (3), even though
small intestinal epithelial cells are exposed to
much higher levels of environmental mutagens
than are cells within the brain, which are protected by the blood-brain barrier.
Another well-studied contributor to cancer is
inherited genetic variation. However, only 5 to
10% of cancers have a heritable component
(6–8), and even when hereditary factors in predisposed individuals can be identified, the way in
which these factors contribute to differences in
cancer incidences among different organs is
obscure. For example, the same, inherited mutant
APC gene is responsible for both the predisposition to colorectal and small intestinal cancers
sciencemag.org SCIENCE
Downloaded from on March 11, 2016
leads to Cdc48 recruitment for extraction and
degradation of the incomplete translation product.
Rqc2p, through specific binding to Ala(IGC) and
Thr(IGU) tRNAs, directs the template-free and
40S-free elongation of the incomplete translation product with CAT tails. CAT tails induce a
heat shock response through a mechanism that
is yet to be determined.
Hypomorphic mutations in the mammalian
homolog of LTN1 cause neurodegeneration in
mice (21). Similarly, mice with mutations in a central nervous system–specific isoform of tRNAArg
and GTPBP2, a homolog of yeast Hbs1 which
works with PELOTA/Dom34 to dissociate stalled
80S ribosomes, suffer from neurodegeneration
(22). These observations reveal the consequences
that ribosome stalls impose on the cellular economy. Eubacteria rescue stalled ribosomes with
the transfer-messenger RNA (tmRNA)–SmpB system, which appends nascent chains with a unique
C-terminal tag that targets the incomplete protein product for proteolysis (23). The mechanisms
used by eukaryotes, which lack tmRNA, to recognize and rescue stalled ribosomes and their
incomplete translation products have been unclear. The RQC—and Rqc2p’s CAT tail tagging
mechanism in particular—bear both similarities
and contrasts to the tmRNA trans-translation
system. The evolutionary convergence upon distinct mechanisms for extending incomplete nascent chains at the C terminus argues for their
importance in maintaining proteostasis. One advantage of tagging stalled chains is that it may
distinguish them from normal translation products
and facilitate their removal from the protein pool.
An alternate, not mutually exclusive, possibility
is that the extension serves to test the functional
integrity of large ribosomal subunits, so that the
cell can detect and dispose of defective large subunits that induce stalling.
RE S EAR CH | R E P O R T S
in familial adenomatous polyposis (FAP) syndrome
patients, yet cancers occur much more commonly
in the large intestine than in the small intestine
of these individuals.
If hereditary and environmental factors cannot
fully explain the differences in organ-specific cancer risk, how else can these differences be explained?
Here, we consider a third factor: the stochastic
effects associated with the lifetime number of stem
cell divisions within each tissue. In cancer epidemiology, the term “environmental” is generally
used to denote anything not hereditary, and the
stochastic processes involved in the development
and homeostasis of tissues are grouped with external environmental influences in an uninformative way. We show here that the stochastic effects
of DNA replication can be numerically estimated
and distinguished from external environmental
factors. Moreover, we show that these stochastic
influences are in fact the major contributors to
cancer overall, often more important than either
hereditary or external environmental factors.
That cancer is largely the result of acquired
genetic and epigenetic changes is based on the
somatic mutation theory of cancer (9–13) and
has been solidified by genome-wide analyses
(14–16). The idea that the number of cells in a
tissue and their cumulative number of divisions
may be related to cancer risk, making them more
vulnerable to carcinogenic factors, has been proposed but is controversial (17–19). Other insight-
ful ideas relating to the nature of the factors
underlying neoplasia are reviewed in (20–22).
The concept underlying the current work is
that many genomic changes occur simply by
chance during DNA replication rather than as a
result of carcinogenic factors. Since the endogenous mutation rate of all human cell types appears to be nearly identical (23, 24), this concept
predicts that there should be a strong, quantitative
correlation between the lifetime number of divisions among a particular class of cells within each
organ (stem cells) and the lifetime risk of cancer
arising in that organ.
To test this prediction, we attempted to identify tissues in which the number and dynamics
of stem cells have been described. Most cells in
tissues are partially or fully differentiated cells
that are typically short-lived and unlikely to be
able to initiate a tumor. Only the stem cells—
those that can self-renew and are responsible
for the development and maintenance of the tissue's architecture—have this capacity. Stem cells
often make up a small proportion of the total
number of cells in a tissue and, until recently,
their nature, number, and hierarchical division
patterns were not known (25–28). Tissues were
not included in our analysis if the requisite parameters were not found in the literature or if
their estimation was difficult to derive.
Through an extensive literature search, we identified 31 tissue types in which stem cells had been
quantitatively assessed (see the supplementary
materials). We then plotted the total number of
stem cell divisions during the average lifetime of
a human on the x axis and the lifetime risk for
cancer of that tissue type on the y axis (Fig. 1)
(table S1). The lifetime risk in the United States
for all included cancer types has been evaluated
in detail, such as in the Surveillance, Epidemiology, and End Results (SEER) database (3). The
correlation between these two very different
parameters—number of stem cell divisions and
lifetime risk—was striking, with a highly positive
correlation (Spearman’s rho = 0.81; P < 3.5 × 10−8)
(Fig. 1). Pearson’s linear correlation 0.804 [0.63
to 0.90; 95% confidence interval (CI)] was equivalently significant (P < 5.15 × 10−8). One of the
most impressive features of this correlation was
that it extended across five orders of magnitude,
thereby applying to cancers with enormous differences in incidence. No other environmental or inherited factors are known to be correlated in this
way across tumor types. Moreover, these correlations were extremely robust; when the parameters
used to construct Fig. 1 were varied over a broad
range of plausible values, the tight correlation remained intact (see the supplementary materials).
A linear correlation equal to 0.804 suggests
that 65% (39% to 81%; 95% CI) of the differences
in cancer risk among different tissues can be explained by the total number of stem cell divisions
in those tissues. Thus, the stochastic effects of
Fig. 1. The relationship between the number of stem cell divisions in the lifetime of a given tissue and the lifetime risk of cancer in that tissue.
Values are from table S1, the derivation of which is discussed in the supplementary materials.
SCIENCE sciencemag.org
Corrected 23 January 2015; see full text.
2 JANUARY 2015 • VOL 347 ISSUE 6217
79
R ES E A RC H | R E PO R TS
The incorporation of a replicative component as
a third, quantitative determinant of cancer risk
forces rethinking of our notions of cancer causation. The contribution of the classic determinants
(external environment and heredity) to R-tumors
is minimal (Fig. 1). Even for D-tumors, however,
replicative effects are essential, and environmental
and hereditary effects simply add to them. For example, patients with FAP are ~30 times as likely
to develop colorectal cancer than duodenal cancer
(Fig. 1). Our data suggest that this is because there
are ~150 times as many stem cell divisions in the
colon as in the duodenum. The lifetime risk of
colorectal cancer would be very low, even in the
presence of an underlying APC gene mutation, if
colonic epithelial stem cells were not constantly
dividing. A related point is that mice with inherited
APC mutations display the opposite pattern: Small
intestinal tumors are more common than large intestinal tumors. Our analysis provides a plausible
explanation for this striking difference between
mice and men; namely, in mice the small intestine
undergoes more stem cell divisions than the large
intestine (see the supplementary materials for the
estimates). Another example is provided by melanocytes and basal epidermal cells of the skin, which
are both exposed to the same carcinogen (ultraviolet light) at the identical dose, yet melanomas
are much less common than basal cell carcinomas.
Our data suggest that this difference is attributable
to the fact that basal epidermal cells undergo a
higher number of divisions than melanocytes (see
the supplementary materials for the estimates).
The total number of stem cells in an organ and
their proliferation rate may of course be influenced
by genetic and environmental factors such as
those that affect height or weight.
DNA replication appear to be the major contributor to cancer in humans.
We next attempted to distinguish the effects of
this stochastic, replicative component from other
causative factors—that is, those due to the external environment and inherited mutations. For
this purpose, we defined an “extra risk score”
(ERS) as the product of the lifetime risk and the
total number of stem cell divisions (log10 values).
Machine learning methods were employed to
classify tumors based only on this score (see the
supplementary materials). With the number of
clusters set equal to two, the tumors were classified in an unsupervised manner into one cluster with high ERS (9 tumor types) and another
with low ERS (22 tumor types) (Fig. 2).
The ERS provides a test of the approach described in this work. If the ERS for a tissue type is
high—that is, if there is a high cancer risk of that
tissue type relative to its number of stem cell
divisions—then one would expect that environmental or inherited factors would play a relatively more important role in that cancer’s risk
(see the supplementary materials for a detailed
explanation). It was therefore notable that the
tumors with relatively high ERS were those with
known links to specific environmental or hereditary risk factors (Fig. 2, blue cluster). We refer to
the tumors with relatively high ERS as D-tumors
(D for deterministic; blue cluster in Fig. 2) because deterministic factors such as environmental
mutagens or hereditary predispositions strongly
affect their risk. We refer to tumors with relatively low ERS as R-tumors (R for replicative;
green cluster in Fig. 2) because stochastic factors,
presumably related to errors during DNA replication, most strongly appear to affect their risk.
In formal terms, our analyses show only that
there is some stochastic factor related to stem cell
division that seems to play a major role in cancer
risk. This situation is analogous to that of the
classic studies of Nordling and of Armitage and
Doll (10, 29). These investigators showed that the
relationship between age and the incidence of cancer was exponential, suggesting that many cellular
changes, or stages, were required for carcinogenesis. On the basis of research since that time, these
events are now interpreted as somatic mutations.
Similarly, we interpret the stochastic factor underlying the importance of stem cell divisions to be
somatic mutations. This interpretation is buttressed by the large number of somatic mutations
known to exist in cancer cells (14–16, 30).
Our analysis shows that stochastic effects associated with DNA replication contribute in a
substantial way to human cancer incidence in
the United States. These results could have important public health implications. One of the
most promising avenues for reducing cancer
deaths is through prevention. How successful can
such approaches be? The maximum fraction of
tumors that are preventable through primary
prevention (such as vaccines against infectious
agents or altered lifestyles) may be evaluated
from their ERS. For nonhereditary D-tumors,
this fraction is high and primary prevention could
make a major impact (31). Secondary prevention,
obtainable in principle through early detection,
could further reduce nonhereditary D-tumor–
related deaths and is also instrumental for reducing hereditary D-tumor–related deaths. For
R-tumors, primary prevention measures are not
likely to be as effective, and secondary prevention should be the major focus.
4.
5.
6.
7.
8.
9.
10.
11.
Head & neck -1.05
Melanoma -1.62
Pancreatic ductal -3.04
Gallbladder -1.66
Glioblastoma -3.93
Lung non smokers -4.90
Testicular germ cell -4.67
Hepatocellular -6.08
Esophageal -6.14
3.
Ovarian germ cell -6.37
Legs osteosarcoma -7.28
Chronic lymphocytic leukemia -6.89
Acute myeloid leukemia -8.04
Osteosarcoma -7.31
Arms osteosarcoma -10.79
Thyroid medullary -8.61
Head osteosarcoma -12.15
Pelvis osteosarcoma -10.90
Medulloblastoma -14.90
Small intestine -17.68
Duodenum -16.36
Pancreatic islet -17.83
1.
2.
FAP colorectal 18.49
Lynch colorectal 14.86
Lung smokers 7.61
Basal cell carcinoma 11.93
HPV-16 head & neck 6.93
FAP duodenum 4.09
HCV hepatocellular 5.36
Colorectal adenocarcinoma 2.58
-15
-10
-5
Thyroid follicular/papillary 1.05
0
5
10
15
REFERENCES AND NOTES
Fig. 2. Stochastic (replicative) factors versus environmental and inherited factors: R-tumor versus D-tumor classification. The adjusted ERS (aERS) is indicated next to the name of each cancer
type. R-tumors (green) have negative aERS and appear to be mainly due to stochastic effects associated
with DNA replication of the tissues’ stem cells, whereas D-tumors (blue) have positive aERS. Importantly,
although the aERS was calculated without any knowledge of the influence of environmental or inherited
factors, tumors with high aERS proved to be precisely those known to be associated with these factors. For
details of the derivation of aERS, see the supplementary materials.
80
2 JANUARY 2015 • VOL 347 ISSUE 6217
Corrected 23 January 2015; see full text.
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sciencemag.org SCIENCE
RE S EAR CH | R E P O R T S
ACKN OWLED GMEN TS
SUPPLEMENTARY MATERIALS
We thank E. Cook for artwork. This work was supported by the
The Virginia and D. K. Ludwig Fund for Cancer Research, The
Lustgarten Foundation for Pancreatic Cancer Research, The Sol
Goldman Center for Pancreatic Cancer Research, and NIH grants
P30-CA006973, R37-CA43460, RO1-CA57345, and P50-CA62924.
Authors’ contributions: C.T. formulated the hypothesis. C.T. and
B.V. designed the research. C.T. provided mathematical and
statistical analysis. C.T. and B.V. performed research. C.T. and
B.V. wrote the paper.
www.sciencemag.org/content/347/6217/78/suppl/DC1
Materials and Methods
Fig. S1
Table S1
References (32–146)
Jan P. Dumanski,1,2* Chiara Rasi,1,2 Mikael Lönn,3 Hanna Davies,1,2 Martin Ingelsson,4
Vilmantas Giedraitis,4 Lars Lannfelt,4 Patrik K. E. Magnusson,5 Cecilia M. Lindgren,6,7
Andrew P. Morris,6,8 David Cesarini,9 Magnus Johannesson,10 Eva Tiensuu Janson,11
Lars Lind,11 Nancy L. Pedersen,5 Erik Ingelsson,2,11 Lars A. Forsberg1,2*
Tobacco smoking is a risk factor for numerous disorders, including cancers affecting
organs outside the respiratory tract. Epidemiological data suggest that smoking is a
greater risk factor for these cancers in males compared with females. This observation,
together with the fact that males have a higher incidence of and mortality from most
non–sex-specific cancers, remains unexplained. Loss of chromosome Y (LOY) in blood cells
is associated with increased risk of nonhematological tumors. We demonstrate here that
smoking is associated with LOY in blood cells in three independent cohorts [TwinGene:
odds ratio (OR) = 4.3, 95% confidence interval (CI) = 2.8 to 6.7; Uppsala Longitudinal
Study of Adult Men: OR = 2.4, 95% CI = 1.6 to 3.6; and Prospective Investigation of the
Vasculature in Uppsala Seniors: OR = 3.5, 95% CI = 1.4 to 8.4] encompassing a total of
6014 men. The data also suggest that smoking has a transient and dose-dependent
mutagenic effect on LOY status. The finding that smoking induces LOY thus links a
preventable risk factor with the most common acquired human mutation.
T
obacco smoking killed ~100 million people
during the 20th century and is projected to
kill ~1 billion people during the current
century, assuming that the current frequency of smoking is retained (1, 2). Lung
cancer is the prime cause of cancer-associated
death in relation to smoking. However, smoking
is also a risk factor for tumors outside the respiratory tract, and these are more common in males
than females [hazard ratio in males: 2.2, 95% confidence interval (CI) = 1.7 to 2.8; in females: 1.7,
95% CI = 1.4–2.1] (2). Moreover, males have a
higher incidence and mortality from most non–
1
Department of Immunology, Genetics and Pathology,
Uppsala University, Uppsala, Sweden. 2Science for Life
Laboratory, Uppsala University, Uppsala, Sweden. 3Södertörn
University, School of Life Sciences, Biology, Huddinge,
Sweden. 4Department of Public Health and Caring Sciences,
Uppsala University, Uppsala, Sweden. 5Department of
Medical Epidemiology and Biostatistics, Karolinska Institutet,
Stockholm, Sweden. 6Wellcome Trust Centre for Human
Genetics, University of Oxford, Oxford, UK. 7Broad Institute
of Massachusetts Institute of Technology and Harvard
University, Cambridge, Massachusetts, USA. 8Department of
Biostatistics, University of Liverpool, Liverpool, UK. 9Center for
Experimental Social Science, New York University, New York,
NY 10012, USA. 10Department of Economics, Stockholm School
of Economics, Stockholm, Sweden. 11Department of Medical
Sciences, Uppsala University, Uppsala, Sweden.
*Corresponding Author. E-mail: [email protected] (J.P.D.);
[email protected] (L.A.F.).
SCIENCE sciencemag.org
sex-specific cancers, disregarding smoking status, and this fact is largely unexplained by known
risk factors (3, 4). A recent analysis of noncancerous blood cells revealed that a male-specific chromosomal aberration, acquired mosaic loss of
chromosome Y (LOY), is associated with an increased risk of nonhematological tumors among
aging males (5).
Here, we analyzed possible causes of LOY by
studying 6014 men from three independent prospective cohorts—TwinGene, n = 4373 (6, 7); Uppsala
Longitudinal Study of Adult Men (ULSAM), n =
1153 (8); and Prospective Investigation of the
Vasculature in Uppsala Seniors (PIVUS), n = 488
(9)—from which comprehensive epidemiological
records are available (tables S2 to S4). We included the following environmental, lifestyle, and
clinical factors in the analyses: smoking, age, hypertension, exercise habits, diabetes, body mass
index, low-density lipoprotein cholesterol, highdensity lipoprotein cholesterol, education level,
and alcohol intake. We also included genotyping
quality as a confounder in the regression analyses, to adjust for possible influence of experimental noise. Similar definitions of factors were
used in all cohorts, as outlined in tables S2 to S5
and described in detail in the materials and
methods section of the supplementary materials. Estimation of LOY was based on singleCorrected 23 January 2015; see full text.
0.2
Smoking is associated with mosaic
loss of chromosome Y
nucleotide polymorphism (SNP)–array data using
the 2.5MHumanOmni and HumanOmniExpress
beadchips in the ULSAM and PIVUS/TwinGene
studies, respectively (fig. S1). The estimation of
the degree of mosaicism and scoring of LOY was
undertaken using the continuous median logR
ratio (mLRR-Y) estimate, calculated from SNParray data as the median of the logR ratio of all
SNP probes within the male-specific part of chromosome Y (MSY), as described previously (5). An
mLRR-Y estimate close to zero indicates a normal chromosome Y state, whereas more negative mLRR-Y values denote an increasing level
of blood cells with LOY. To facilitate comparisons between the three cohorts, we corrected the
mLRR-Y values for all participants, using cohortspecific correction constants, as explained in the
supplementary materials (figs. S1 and S2).
LOY was by far the most common postzygotic
mutation found in the three cohorts. The age
range at sampling in ULSAM and PIVUS was
70.7 to 83.6 years and 69.8 to 70.7 years, respectively, and we found LOY in 12.6% of ULSAM
participants and 15.6% of PIVUS participants
(figs. S3 and S4). The age range at sampling in
TwinGene was 48 to 93 years, and the frequency
of LOY in the entire cohort was 7.5% (fig. S5).
***
***
*
0
MUTAGENESIS
4 September 2014; accepted 20 November 2014
10.1126/science.1260825
mLRR-Y
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-0.2
25.
n=3507 n=634 n=892 n=218
No Yes
TwinGene
No Yes
ULSAM
n=439 n=48
No Yes
PIVUS
Fig. 1. The association between smoking status
and the level of LOY (i.e., mLRR-Y) in three independent cohorts. In all cohorts, these unadjusted
analyses indicate that the current smokers (Yes)
(table S5) had a significantly higher degree of
mosaic LOY in blood, compared with noncurrent
smokers (No), composed of never-smokers and previous smokers. ***P < 0.001; *P < 0.05 (KolmogorovSmirnov tests: TwinGene, D = 0.15, P = 1.131× 10–11;
ULSAM, D = 0.15, P = 0.0006; PIVUS, D = 0.23, P =
0.0203). The definitions used for LOY scoring and
the entire ranges of mLRR-Ydata observed in each
cohort are shown in figs. S3 to S5.
2 JANUARY 2015 • VOL 347 ISSUE 6217
81
Variation in cancer risk among tissues can be explained by the
number of stem cell divisions
Cristian Tomasetti and Bert Vogelstein
Science 347, 78 (2015);
DOI: 10.1126/science.1260825
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